Using reliable data to convert prospects and make sales

Using reliable data to convert prospects and make sales

Sales, much like most business disciplines, is a numbers game. Sure, you need a quality product or service as well as a top-notch staff and sales team, but you also need to understand how to maximize the odds so that they are in your favor when it comes to converting prospects via a call center. The concept of conversion rates has long been used in the marketing sphere, but is now being recognized as a benchmark for success in outbound sales call centers as well. Reliable leads are the crucial component of maximizing a call center’s conversion rate. However, before understanding how one maximizes their conversion rate, it is crucial to understand the building blocks of the conversion rate system as used as a success benchmark.

Marketing conversion rates have been used for quite some time to measure the effectiveness of internet marketing campaigns. Simply put, the marketing conversion rate, as defined by Brick Marketing, is measured by the number of potential visitors performing the desired action, whether the action is buying a product, filling out a form, or some other goal such as clicking on an advertisement that takes the visitor to another website. While marketing conversion in its entirety can be a complex concept, the essence of it is rather simple. It doesn’t take a PhD in statistics to understand that the more quality leads one has that the higher their odds of getting a sale. To achieve maximum conversion rates, marketing companies have to target the customers who are most likely to be interested in their product, service, or website. Typically, this is done through the use of working with search engines or social media to target prospects that have used keywords in either their internet searches or social media posts or have visited websites similar to that of the target product or service. Most search engines use a combination of cookies to monitor key phrases and personal user-provided data to identify target customers. For example, a outdoor camping gear company would want to target users in the United States, Canada, and Australia between the ages of 25 and 50 without very young children who have searched for terms such as camping supplies, camping trips, national park camping permits, etc. By filtering data based on age (people with expendable income who are physically able to camp) and interests (in this case outdoor activities and camping), the marketing company is ensuring that their ads are only being shown to higher potential leads rather than an 80 year old woman who primarily uses the internet to email family.

Just like marketing companies need to filter out unlikely prospects, call centers need to filter out bad data as well. If an online camping equipment retailer posted a general Internet ad for camping equipment with everyone in the world as an audience and hoped that someone was interested, then the results would be poor. The ad would be shown to people who don’t speak English, people who are very old, people who have young children that get couldn’t take camping, and people who don’t even like the outdoors. Clearly, this would be an inefficient method and would result in lower conversion rates than a targeted marketing campaign.

By the same token, if sales people at a call center simply called every number on a prepaid list, it would be akin to the above scenario and fewer sales would be made. The list would be filled with bad numbers, people who are not ideal candidates for the product or service, and people who are not financially qualified. Even worse, the lists might not be TCPA compliant, potentially landing your company in hot water.

Depending on your volume RealValidation phone validation service cost can be below a penny a number, and there’s no upfront fee, so it’s easy to make data quality a priority and make the marketing budget go further.

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